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## Warning: Column `country` joining character vector and factor, coercing
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## We recommend that you use the dev version of ggplot2 with `ggplotly()`
## Install it with: `devtools::install_github('hadley/ggplot2')`
## Computing profile confidence intervals ...
## Warning in profile.merMod(object, which = parm, signames = oldNames, ...):
## non-monotonic profile for age
## Warning in profile.merMod(object, which = parm, signames = oldNames, ...):
## non-monotonic profile for wealthindex
## Warning in optwrap(optimizer, par = thopt, fn = mkdevfun(rho, 0L), lower
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## Warning in profile.merMod(object, which = parm, signames = oldNames, ...):
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## Warning in profile.merMod(object, which = parm, signames = oldNames, ...):
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## Warning in profile.merMod(object, which = parm, signames = oldNames, ...):
## non-monotonic profile for Number.of.children.5.and.under
## Warning in if (parm == "theta_") {: the condition has length > 1 and only
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## Warning in confint.thpr(pp, level = level, zeta = zeta): bad spline fit for
## age: falling back to linear interpolation
## Warning in confint.thpr(pp, level = level, zeta = zeta): bad spline fit for
## wealthindex: falling back to linear interpolation
## Warning in confint.thpr(pp, level = level, zeta = zeta): bad spline fit for
## has_bednet: falling back to linear interpolation
## Warning in confint.thpr(pp, level = level, zeta = zeta): bad spline fit for
## livechl: falling back to linear interpolation
## Warning in confint.thpr(pp, level = level, zeta = zeta): bad spline fit for
## Number.of.children.5.and.under: falling back to linear interpolation
## Currently generic markdown table using pandoc is not supported.
Estimates and confidence intervals
term estimate std.error statistic X2.5.. X97.5..
age 0.2151484 0.0026919 79.925408 0.2151484 0.2151547
wealthindex 1.2195821 0.0388218 31.414843 1.2195820 1.2196709
has_bednet 0.8266771 0.1072061 7.711102 0.8266769 0.8269203
livechl 0.1017296 0.0220738 4.608604 0.1017296 0.1017797
Number.of.children.5.and.under -0.2377546 0.0361338 -6.579845 -0.2377547 -0.2376729